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qualms about a bond market for philanthropy

Today’s New York Times describes a nascent plan for a philanthropic bond market. The main proponent, Lindsay Beck, “says she has long believed that charitable money is often misallocated; some of the most effective organizations struggle to raise funds, while some of the least effective charities are allocated millions.” She proposes that people and firms that want to do good with their money (and gain tax advantages) should buy bonds in nonprofits that show strong evidence of effectiveness.

This proposal is just an example of the broader movement toward social entrepreneurship, social impact investing, and (more generally) the application of business principles to philanthropy. It makes sense insofar as nonprofits provide services with market value that their clients cannot afford. For example, a homeless person could and would buy a meal if he had the cash. If a nonprofit provides the meal for free, funders naturally want to know how many meals they can buy for their dollar.

But there’s another way to look at nonprofits: as associations created, managed, and sustained by citizens in their communities. De Tocqueville thought that democracy flourished in America only because we had such associations to complement the state and the market.

Investing in nonprofits to deliver services ignores these issues:

1. Power. Of course, the golden rule has always applied (“He who has the gold, rules”). But traditionally, if you wanted to be a philanthropist in your community, you had to meet with leaders of civic groups, and they’d have agendas of their own. You had the cash, but they would be able to bestow positive or negative publicity. Their members could vote in local elections that would affect your interests. They would have relationships with other organizations in town, from the newspaper to the church. You could not just get up and leave town without substantial costs. There was some power on both sides of the table, which meant that they could decide what they wanted and ask you for it. In a philanthropic bond market, all the power lies with the donor.

2. Learning: In a traditional nonprofit, the leaders and other members decide what they want to do. They deliberate and learn from practical experience. That means they can fail, or face internal conflicts, or apply bad values. It also means that they learn the Tocquevillian art and science of association, and they can transfer their learning to other organizations and to politics. On the other hand, in a philanthropic market, social entrepreneurs create products and sell them to investors. Very few people learn, and no one must learn how to reason and negotiate with people who lack money and power.

3. Social capital: My colleagues Kei Kawashima-Ginsberg and Chaeyoon Lim and I have found that communities have better economic prospects if they have more nonprofit organizations per capita. We argue that it’s not because the nonprofits provide goods and services efficiently. In fact, fewer, bigger nonprofits might be more efficient. It is rather that participants in hands-on local associations develop networks, relationships, and loyalties that are valuable economically. If investments flow to highly efficient nonprofits, then social capital will be wiped out.

4. Value questions. It is not self-evident that we should reduce recidivism (which is the example cited in the Times article). Maybe we should fight to cut the arrest and incarceration rates instead. A program to cut recidivism offers a service that can be quantified and measured: $x reduces the prison-return rate by y%. It thereby legitimizes the criminal justice system. I am not necessarily in favor of more radical changes, but I think they should be discussed, and the decision should not be made by the people with cash. Again, I realize that wealthy donors have always had disproportionate power, but a bond market just takes away all the friction and resistance. Donors can buy a lower recidivism rate (while taking tax benefits) without any accountability for the moral tradeoffs and complexities.

5. Process. If you believe in democracy at all, you believe in certain processes for making decisions collectively. These processes vary, but in general, they involve a degree of deliberation and some equality in the power to determine the outcomes. Democratic processes are inefficient. They slow down service-delivery and they impose their own costs. (Someone has to pay for the meeting rooms, the snacks, the facilitation, and the recruitment.) To the extent that philanthropists can pay for pure outcomes, they will not invest in processes. And then we will have fewer meetings and other democratic processes in our communities.

I suppose we can have a bond market for investments in pure service-delivering nonprofits and also an array of locally rooted, deliberative associations that control their own destinies. But I worry that the money, attention, and energy will shift to the former and the Tocquevillian basis of our democracy will continue to erode.

CIRCLE press release on youth turnout in Virginia and New Jersey

(cross-posted from the CIRCLE website) If the Virginia and New Jersey exit polls captured precise and accurate estimates of the proportion of voters who were young, then youth turnout was 26% in Virginia and 18% in New Jersey, according to CIRCLE’s calculations.* In recent elections, exit polls have not always captured accurate age demographics. Also, the preliminary exit poll results reported on Election Day are subject to revision. However, CIRCLE’s turnout estimates are based on the best available data.

Using the same methods, we calculated that youth turnout in Virginia was 17% in 2009 and 18% in 1997, and in New Jersey 26% in 1997 and 19% in 2009.  That suggests a significant rise in Virginia this year.

Table 1: Turnout in Gubernatorial Elections, ages 18-29*

1997 2009 2013
New Jersey 26% 19% 18%
Virginia 18% 17% 26%

These turnout estimates would translate to roughly  288,000 young voters who cast a ballot yesterday in Virginia, out of the estimated 1.1 million 18-29 year-old citizens who live in that state.  In New Jersey, roughly 206,000 young voters cast a ballot out of the estimated 1.2 million 18-29 year old citizens.

According to the exit poll, 45% of young people voted for Democratic candidate Terry McAuliffe yesterday in Virginia, 40% for Republican candidate Ken Cuccinelli and 15% for Libertarian Robert Sarvis. In New Jersey, a small majority of young people (51%) voted for Democratic Candidate Barbara Buono but 49% supported incumbent Governor Chris Christie.

As a proportion of all the people who voted, in 2013, under-30s represented 13% in Virginia, which reflects a modest increase from 2009, when they made up 10% of all voters. In New Jersey, under-30s represented 10% of voters, which is very similar to the youth share of 9% in 2009. (The share of voters is not an accurate measure of youth turnout. “Turnout” is the proportion of all young citizens who voted, shown above.)

“Although 18% and 26% percent are far from satisfactory, these statistics should be put in context,” said CIRCLE Director Peter Levine. “Turnout is always much lower in off-year gubernatorial elections than in presidential years. The best available evidence on Virginia’s youth turnout suggests an increase compared to the two most recent gubernatorial races there. Virginia is also interesting in that Barack Obama won the state’s youth vote easily, but Democrat Terry McAuliffe got less than half of youth, and Libertarian Robert Sarvis ran relatively strong at 15%.”

* The estimated numbers of young people who voted in the 1997 and 2009 governors’ races were calculated using: (1) the number of ballots cast in each race according to the media, (2) the youth share of those who voted, based on the exit polls conducted by Edison Research for the National Election Pool, and (3) the estimated number of 18-29 year old citizens taken from the Census Current Population Survey, March Demographic File of that year.  Edison Research estimates that its exit polls have a margin of error rate of plus or minus three percentage points.

strange lives

I surf Wikipedia looking for interesting stories, so you don’t have to. For instance:

Charles deRudio/Carlo di Rudio is born an Italian aristocrat in 1832. After fighting for Italian unification, he flees the country and is shipwrecked off Spain. We next meet him living in East London with his Cockney wife Eliza. In 1858, he is one of several men who throw innovative, mercury-based bombs at the Emperor Napoleon III, killing eight people but not harming the monarch. DiRudio is sentenced to be guillotined but spared and sent instead to the notorious Devil’s Island, off today’s Suriname. He escapes from there and immigrates to the US. During the Civil War, he serves as a Second Lieutenant, commanding Black troops. He stays in the US Army after the war and fights in the Battle of Little Binghorn, at which George Custer and most of his men are killed. DeRudio and one other man survive by hiding in a copse for 36 hours while Lakota women attack the bodies of the US Cavalry. DeRudio dies in Pasadena in 1910.

An anonymous Irish monk works at Reichenau Abbey, now in Alpine Germany, during the 9th century. He writes a poem in Old Irish about his companionable cat, Pangur Bán, which is translated by W.H. Auden and Seamus Heaney, among others, and set to music by Samuel Barber.

In 1943, Hans Robert Lichtenberg is born to the chief of police of wartime Frankfurt. In 1980, at age 36, he is adopted by Princess Marie-Auguste of Anhalt, daughter-in-law of the late and deposed German Emperor Wilhelm II. There are allegations that the adoption, which makes him “Prinz von Anhalt,” is arranged for cash. At age 43, he marries the 69-year old Zsa Zsa Gabor. They adopt three grown men, who inherit various titles. In 2007, three women allegedly approach “Prinz von Anhalt,” ask to pose in a picture with him, pull out guns, and steal his Rolls-Royce, jewelry, wallet, and all his clothes, leaving him naked when the police arrive. In 2010, he runs for Governor of California.

The king of India learns that his son Josaphat is planning to become a Christian. He isolates him from the world, but a Christian hermit saint named Barlaam gets access to Josaphat and converts him. The king relents and abdicates in favor of Josaphat who, after reigning for some time, leaves with Barlaam to become a wandering saint. In all probability, this is actually the foundational Buddhist story of Siddhartha Gautama, translated from Sanskrit into Persian (by Manicheans), which is then translated into Arabic as the “Book of Bilawhar and Yudasaf,” which influences the Georgian Orthodox and Catholic churches to recognize a pair of saints. The Sanskrit title bodhisattva (saint) probably becomes the name Josaphat by way of “bodisav” in Persian, Budhasaf or Yudasaf in Arabic, Iodasaph in Georgian, Iodasaph in Greek, and lastly Josaphat in Latin.

radio discussions of We Are The Ones We Have Been Waiting For

These are scheduled radio interviews on my new book:

Thursday, October 24, 2013, 6:40 – 6:50AM
New York City
live interview on the “John Gambling Show,” WOR-AM

Friday, October 25, 2013, 9:00 – 10:00AM
Hartford, CT
live interview with call-ins (WNPR-FM)

Tuesday, November 5, 2013, 2:00-3:30PM Central (local) time
Wisconsin and upper Midwest
live with call-ins: “Conversations w/Kathleen Dunn”

Tuesday, November 12, 2013, 1:00-2:00PM
Miami
live interview on “Tropical Currents, WRLN 93.1FM

Wednesday, November 13, 2013, 2:00 – 3:00pm Pacific (local) time
Seattle
live interview: KUOW-FM

epistemic network analysis and morality: applying David Williamson Shaffer’s methods to ethics

David Williamson Shaffer and his colleagues are developing an influential approach to education and assessment that relies on the notion of “Epistemic Network Analysis.” They posit that a “profession or other socially valued practice” (e.g., engineering) has an “epistemic frame” that is composed of many facts, skills, values, identities, and other concepts that advanced practitioners link together in various ways. Thus you can diagram a professional’s epistemic frame as a network and measure it using tools that have been developed for measuring social networks. What nodes are most central? How dense is the whole network? How many clusters does it have?

One way to collect the data necessary for this kind of analysis is to ask a practitioner to write or talk about her work. Many of her sentences will invoke concepts and link them together. (“I did A because I knew that B.” “I recommend C because I believe in ethical norm D.”) By coding the text, one can produce a dataset that can be displayed and analyzed in network terms. As Shaffer and colleagues note, the graph is not the actual epistemic network; it is a representation of how the engineer’s mentality works under specific practical circumstances (Shaffer et al, 2009, p. 14).

If a profession is worthy, then learning its epistemic frame is desirable. As students experience a course, a project, or an internship, their epistemic frames can be diagrammed and quantified at regular intervals. The learners’ networks should grow more similar to those of advanced professionals. Measures of network structure can be used for “formative assessment” (giving feedback on what the student should study) and “summative assessment” (awarding a grade or credential).

I have posited that moral thinking is also an epistemic frame (to use Shaffer’s terminology). We hold many morally relevant ideas that we connect by various kinds of links, not just logical inferences but also causal theories, generalizations, analogies, etc. We can graph our own moral mentality as a network of ideas and connections. Moral learning means building a moral network map that resembles that of a good moral thinker. (I leave aside for now the question of whether good moral reasoning is related to good moral behavior.)

One can easily see that the moral network map of an average adult is more complex than that of a 2-year-old. It is uncontroversial that a toddler needs to learn to reason more maturely, in which case his network map will look more like yours and mine. But that leaves a lot of room for debate about what an ideal map looks like. Defining good moral thought is a normative, not an empirical, question.

To some extent, that is also true of engineering. It is not self-evident what makes a “good” engineer. However, as long as we assume that the profession is working reasonably well and fulfilling its social purposes adequately, then a “good” engineer is presumably a respected and successful one. We can identify such people empirically: they have high grades, awards, and responsible positions. Then we can diagram their epistemic frames and compare novices to exemplary professionals to assess their learning.

The situation is much harder with morality. We debate what specific moral concepts and relationships should be found on a person’s epistemic frame. For instance, should everyone’s graph show the existence of God, linked to a set of commandments? We also debate what formal properties any moral network should display. Should it be highly centralized around one fundamental truth? Classical utilitarians and some religious fundamentalists would say so. Or should it be very flat and complex, as certain liberals have held?

Here I would introduce a controversial–but not original–premise that makes the identification of good moral networks somewhat more empirical. No human being can have a fully adequate moral theory in place before she faces the various situations of life. The moral world is far too complex for that. It involves countless differently situated people interacting in countless situations in relation to institutions (like education, romance, politics, and punishment, to name a few) that have evolved to have manifold purposes and meanings. So to think well morally is not to apply a theory to each new case, but rather to learn constantly. Learning results from interactions with other people (whether face-to-face or vicariously). By “interaction,” I do not mean only communication, or the exchange of ideas. Groups of people can agree on thoroughly foolish ideas unless they try to put them into practice. So “interaction” means a combination of exchanging ideas, trying to work together, and reflecting on the results–what Dewey often called “conjoint activity.”

Who is good at that? This is not strictly an empirical question, because we might disagree about how to assess various styles of interaction. Should we admire the persuasive ideologue? The follower of fads? But although value-judgments are inescapable, I think it is partly an empirical question who participates constructively in conjoint activity. Good participants do not impose preexisting ideas and do not merely adopt the majority’s view, but shape the group’s beliefs while adjusting their own.

As I have written before, my own unsystematic observation suggests that people who are better at moral interaction have epistemic networks with these features:

  1. Lots of nodes and links, because each idea is an entry point for dialogue, and each reflects some prior learning.
  2. A degree of centrality, because some moral ideas are genuinely more important than others; and also because one should develop a set of prized values that constitute your character. Yet:
  3. No outright dependence on a small set of nodes to hold the whole network together, because then disagreement about those nodes must end a conversation, and doubt about them will plunge you into nihilism. You may believe in fundamental principles, but you should be able to reason around them. The network should be robust in that sense.

We might try to identify the actual epistemic frames of people who are good at collaboration and deliberation and see if they manifest the three features I listed above. We could then map the networks of children and other moral learners to see if they are developing to resemble the exemplary cases. Again, this would not be a value-neutral research program, but it would have a strong empirical component.

We can, in fact, pursue three levels of analysis.

  1. Each individual has an evolving and not-fully-conscious epistemic frame composed of many ideas and connections.
  2. The individual belongs to a community of other people who all have networks of their own. Their networks overlap and influence each other because moral learning is social. (Even a recluse got his ideas from someone else). Within a community, individuals’ maps intersect in a second way as well. If one person has a moral commitment to a specific other person, that other will appear on her map.
  3. Finally, the world is composed of many moral communities. But these are never fully separate and distinct. They are always complex, overlapping, and vaguely-bordered networks. Given two entities that we call “cultures,” no matter how remote, we will likely find common nodes and connections in their respective moral networks. I leave aside the possibility that all human beings share a set of ideas as our biological inheritance. That may be the case, but I do not rely on it. Rather, all communities interact (even the so-called “uncontacted peoples” who live deep in rain forests), and so the members of community A always share some nodes with members of community B nearby as a result of their “conjoint activity.”

At the individual, community, and global level, the process of moral reasoning is fundamentally the same. It is always a matter of developing a more satisfactory network of ideas and connections. This is not easy, conflict-free, or pretty. Individuals face deep internal conflicts among incompatible ideas, and people and communities often actually kill each other on account of such disagreements. Nevertheless, we can point to individuals and groups that are better at constructive engagement, and moral learning means becoming more like them.

Reference: David Williamson Shaffer, David Hatfield, Gina Navoa Svarovsky, Padraig Nash, Aran Nulty, Elizabeth Bagley, Ken Frank, Andre A. Rupp, and Robert Mislevy, “Epistemic Network Analysis: A Prototype for 21st Century Assessment of Learning,” International Journal of Learning and Media, vol. 1, no. 2 (2009), pp. 1-22.